Background: Tissue engineering is a strategy of cartilage regeneration, but scaffolds, required for 3D growth of chondrocytes, are still a problem. Methods: Searching for possibilities to improve scaffold-free engineering of cartilage, we characterized human chondrocytes incubated on a random positioning machine (RPM) to simulate microgravity (µg). Results: When cultured in simulated µg, human chondrocytes start forming 3D cell assemblies within 5 days. After 24h, we could not detect caspase-3, Fas, p53 or Bcl-2 proteins in these cells, Annexin V flow cytometry, however, revealed 18% of apoptotic chondrocytes in 1g cultures but only 10% on the RPM. Both rates of apoptosis were not changed, when vascular endothelial growth factor (VEGF) or basic fibroblast growth factor (bFGF) was added. 24 h, simulated microgravity also had significantly decreased collagen type I and X, but did not change collagen type IV and laminin, while collagen type II, chondroitin sulfate and aggrecan were elevated as compared with 1g controls. The production of collagen type II/X, chondroitin sulfate and aggrecan was modified, when external bFGF or VEGF had been applied. Conclusion: Chondrocytes exposed to simulated µg seem to change their extracellular matrix production behavior, while they rearrange their cytoskeletal proteins prior to forming 3D aggregates.

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Objective: A systematic review and meta-analysis of diagnostic biomarkers for noninvasive diagnosis of acute allograft rejection following liver transplantation. Background: Noninvasive blood and urine markers have been widely explored in recent decades for diagnosing acute rejection after liver transplantation. However, none have been translated into routine clinical use so far due to uncertain diagnostic accuracy, and liver biopsy remains the gold standard. Methods: Systematic literature searches of Medline, Cochrane and Embase were conducted up to February 2019 to identify studies evaluating the use of noninvasive markers in diagnosing allograft rejection following liver transplantation. Meta-analysis was performed using a random effects model with DerSimonian–Laird weighting and the hierarchical summary receiver operating curve. Results: Of 560 identified studies, 15 studies (1,445 patients) met the inclusion criteria. The following markers were tested: acid labile nitroso-compounds (NOx), serum amyloid A protein, procalcitonin, peripheral blood eosinophil count, peripheral blood T-cell activation and interleukin 2 (IL-2) receptor, guanylate-binding protein-2 mRNA, graft-derived cell-free DNA, pi-glutathione S-transferase, alpha-glutathione S-transferase and serum HLA class I soluble antigens. Only eosinophil count was tested in multiple studies, and they demonstrated high heterogeneity ( I 2 = 72% [95% CI: 0.5–0.99]). IL-2 receptor demonstrated the highest sensitivity (89% [95% CI: 0.78–0.96]) and specificity (81% [95% CI: 0.69–0.89]). Conclusion: IL-2 receptor expression demonstrated the highest diagnostic accuracy, while the peripheral eosinophil count was the only marker tested in more than one study. Presently, liver biopsy remains superior to noninvasive diagnostic biomarkers as most studies exhibited inferior designs, hindering possible translation into clinical application.

The diagnosis of acute cellular rejection (ACR) after liver transplantation is based on histological analysis of biopsies because noninvasive biomarkers for allograft rejection are not yet established for clinical routines. CD31, CD44, and chemokine (C-X-C motif) ligand (CXCL) 9 have previously been described as biomarkers for cross-organ allograft rejection. Here, we assessed the predictive and diagnostic value of these proteins as serum biomarkers for clinically significant ACR in the first 6 months after liver transplantation in a prospective study. The protein levels were measured in 94 patients immediately before transplantation, at postoperative days (PODs) 1, 3, 7, and 14 and when biopsies were performed during episodes of biochemical graft dysfunction. The CD44 serum protein levels were significantly lower at POD 1 in patients who experienced histologically proven ACR in the follow-up compared with patients without ACR (P < 0.001). CXCL9 was significantly higher before transplantation (P 5 0.049) and at POD 1 (P < 0.001) in these patients. Low CD44 values (cutoff, <200.5 ng/mL) or high CXCL9 values (cutoff, >2.7 ng/mL) at POD 1 differentiated between rejection and no rejection with a sensitivity of 88% or 60% and a specificity of 61% or 79%, respectively. The combination of both biomarker cutoffs at POD 1 had a positive predictive value of 91% and a negative predictive value of 67% for clinically significant ACR. Moreover, CD44 was significantly lower at the time of ACR (P < 0.001) and differentiated the rejection group from patients with graft dysfunction due to other reasons. Our results suggest that CD44 and CXCL9 may serve as predictive biomarkers to identify liver allograft recipients at risk for clinically significant ACR.

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